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1476909/2456935/README.md

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-# Penis Lora (+Blowjob, +Cumshot) [Taz]  - WAN 2.2 14b / 5B / 1.3b T2V & I2V (Wan 2.1 & 2.2) + Qwen + Zimage Turbo-ZImage Turbo V1 - 2456935
+# Unknown - 2456935
 
-**Model Type**: LORA
+**Model Type**: Unknown
 
-**Base Model**: ZImageTurbo
+**Base Model**: Unknown
 
 **Trigger Words**: None
 
-**Tags**: style
+**Tags**: None
 
 ## Gallery
 
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 ## Description
 
-About this version (qwen v2)
-
-A brushup of the dataset, with better result than V1 for qwen. I will use the same dataset again for zturbo when the base model is released.
-
-**Trigger word:** PENISLORA
-
-**What can this lora do?**
-
-This lora can add erect penises to both men or women viewed from the front/side. Other angles such as POV may have a backwards penis head.
-
-Other things it can now do:  
-Side view of the penis
-
-Cumming / Cumshots
-
-Blowjobs (its captioned for the words "blowjob" and "deepthroat" )
-
-What can't it do?
-
-No penetration in the training data. Also nothing from POV angle, though there is a few images from above and 1 POV video in the training data.
-
-Sometimes blowjobs with cumming have the penis slip out the closed mouth.
-
-**Recommended Settings**
-
-It works pretty good with the new lightning dyno high model. I'll link to it in my example workflow. I like to use dyno high model (no lightning lora), then for low I use the lightning v2 lora on the regular 2.2 low base model.
-
-**Dataset**
-
-84 images at 512x resolution
-
-43 videos at 256x resolution
-
-(I let DP pick the aspect ratio automatically)
-
-This is the same exact dataset as the 2.2 5B model. I made no changes.
-
-**Training**
-
-I used the default diffusion pipe settings.
-
-[optimizer]
-
-type = 'adamw\_optimi'
-
-lr = 2e-5
-
-betas = [0.9, 0.99]
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-weight\_decay = 0.01
-
-eps = 1e-8
-
-I was baffled why it was taking so long to train the high until I realized after over 60 hours of training that I had put my videos in the images directory which resulted in the high being trained ONLY only on videos and twice (once with a very high resolution). Once I fixed this, I went back and trained from 11K steps up to around 13K with the images in the training data. The high model was fine without to be honest.
-
-For the low, I trained it properly with videos and images the whole way, around 6K steps in I upped the image resolution from 512 to 1024 actually and didn't get an OOM (it fit around 24GB exactly). I trained it to around 10.5K steps. Also I trained the low on the full timestep range (0 to 1 instead of 0 to 0.85) from some advice, it may switch better over from high to low on the speed up lora with low steps.
-
-I think I might do another version with more angles such as POV and from the behind to make this work for any situation. In that case I don't think it needs 10K steps per training session, epochs around 5K steps looked fine.
-
-**The results**
-
-I think it was a combination of improved captioning and 2.2 base model being better. But this lora turned out really well.
+No description available.
 
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-Author: [tazmannner379](https://civitai.com/user/tazmannner379)
+Author: [Unknown](https://civitai.com/user/Unknown)
 
 Model: [CivitAI Model Page](https://civitai.com/models/1476909?modelVersionId=2456935)